There has been a surge of interest in the design and application of unmanned aerial vehicles (UAVs), particularly fixed wing micro-air vehicles (MAV). UAVs can be used in numerous civilian applications, such as urban reconnaissance, package delivery, and area mapping. UAVs are utilized in various military applications as well. While some UAVs require human operators remotely controlling the operation and/or flight path of the UAV, other UAV's have been designed for autonomous operation. One of the biggest challenges involved in the autonomous operation of UAVs is in the design of flight tracking controllers for UAVs, which often operate in uncertain and possibly adverse conditions.
Flight tracking controllers should provide the UAV, operating autonomously, with the ability to remain within an acceptable range of their intended flight path while operating in an uncertain environment caused by, for example, changing wind velocity and direction resulting in gusts, vortical structures and turbulence.
Additionally, suppression of limit cycle oscillations (LCO) (or flutter) is another concern in UAV tracking control design. This is especially true for applications involving smaller, lightweight UAVs, where the aircraft wings are more susceptible to LCO. LCO refers to “flutter” behaviors in UAV wings that manifest themselves as constant-amplitude oscillations, which result from nonlinearities inherent in the aeroelastic dynamics of the UAV system. Note that LCOs may significantly affect the aerodynamic properties of an aircraft, and can be especially devastating for small UAVs interacting with impinging gusts with amplitudes comparable to the vehicle speed. Indeed, the gust-induced wing dynamics results in lift, drag, and pitching-moment oscillations deteriorating the aircraft aerodynamic performance and posing severe challenges to aircraft flight stability. Due to these behaviors, the LCO could surpass the safe flight boundaries of an aircraft and could potentially lead to structural damage causing the UAV to crash.
These engineering challenges necessitate the utilization of UAV flight controllers, which achieve accurate flight tracking in the presence of dynamic uncertainty while simultaneously suppressing LCO. Control applications for LCO suppression have been developed using mechanical deflection surfaces (e.g., flaps, ailerons, rudders, and elevators). However, when dealing with smaller UAVs, practical engineering considerations and physical constraints can preclude the addition of the large, heavy moving parts that generally are required for installation of deflection surfaces.
Due to their small size, ease of operation, and low cost, synthetic jet actuators (SJA) are promising tools for aircraft tracking control and flow control applications. SJA's transfer linear momentum to a flow system by using a vibrating diaphragm, which creates trains of vortices through the alternating ejection and suction of fluid through a small orifice. Since these vortices (i.e., jets) are formed entirely from the fluid (i.e., air) of the flow system, a key benefit of SJA is that they achieve this transfer of momentum with zero net mass injection across the flow boundary. Thus, SJAs do not require space for a fuel supply. SJAs can be utilized to modify the boundary layer flow field near the surface of an aircraft wing, which can improve aerodynamic performance. Moreover, synthetic jet actuators can expand the usable range of angle of attack, which can improve maneuverability. In addition to flow control applications, arrays consisting of several SJAs can be employed to achieve tracking control of aircraft, possibly eliminating the need for mechanical control surfaces. The benefits of utilizing SJAs on aircraft as opposed to mechanical control surfaces include reduced cost, weight, and mechanical complexity.
SJAs have been developed with the capability to achieve momentum transfer with zero-net mass-flux. This beneficial feature eliminates the need for an external fuel supply, since the working substance is simply the gas (i.e., air) that is already present in the environment of operation. This makes SJAs an attractive option in UAV applications, because of the significant reduction in the size of the required equipment. The SJAs synthesize the jet flow through the alternating suction and ejection of fluid through an aperture, which is produced via pressure oscillations in a cavity. The pressure oscillations can be generated using various methods, including pistons in the SJA's orifices or piezoelectric diaphragms. SJA's can achieve boundary-layer flow control near the surface of a UAV wing since they can provide instant actuation, unlike conventional mechanical control surfaces. In addition, SJA's can expand the usable range of angle of attack, resulting in improved UAV maneuverability.
FIGS. 1 and 2 show an example UAV 100 with a seamless fixed wing construction. The UAV 100 includes an airframe 102 and an array of synthetic jet actuators 104 disposed at selected locations around the periphery of the wing of the airframe 102. FIG. 3 schematically illustrates a synthetic jet actuator 104. The SJA includes a cavity 106, a membrane 108, also called a diaphragm, and an outlet orifice 110. The SJA 104 is provided with a voltage to cause the membrane 108 to oscillate, resulting in a time averaged pulsed jet of air being emitted from the orifice 110. The magnitude of the voltage applied to the SJA 104 may impact the flex or force of air expelled from the orifice 110. Under certain conditions, a series of vortex rings 112 formed during the expulsion phase are able to escape the reverse injection and convect away from the orifice as a time-averaged jet capable of manipulating the flight path of the airframe 102 and/or the flow of air affecting the airframe 102.
Use of SJA present challenges in control design due to uncertainties inherent in the dynamics of their operation. Specifically, the input-output (i.e., the control voltage to force delivered) characteristic of each SJA is nonlinear and contains parametric uncertainty. To compensate for this uncertainty, recently developed SJA-based control systems utilize online adaptive control algorithms, neural networks, and/or complex fluid dynamics computations in the feedback loop. FIG. 4 schematically illustrates one control system 200 that the present disclosure seeks to improve. Particularly, the control system 200 includes a processor 202 configured to generate a control command to a set of UAV system dynamics 204, such as an array of synthetic jet actuators. The processor 202 determines the controller command based on part on sensor measurements 206 which form a first feedback loop 208 to the processor 202. The instant control system 200 is characterized by the use of an adaptive parameter update law 210, effectively requiring a second feedback loop 212 such that the processor 202 generates the controller command based on a control law which is required to adapt or update itself with each iteration. However, implementation of these computationally burdensome control techniques, i.e., the adaptive parameter update law 210 and second feedback loop 212 requires additional computational resources (e.g., microprocessors, timer circuits, and/or time-consuming processing algorithms), which might not be available for smaller UAV applications with limited onboard space and computing power. Moreover, the computational complexity in these control system designs results in a slower control response rate, which can hinder control performance or even cause catastrophic failures.